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The Gross Domestic Product per capita in the United States was last recorded at 66682.61 US dollars in 2024. The GDP per Capita in the United States is equivalent to 528 percent of the world's average. This dataset provides - United States GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.
In 2023, the real median household income in the state of Alabama was 60,660 U.S. dollars. The state with the highest median household income was Massachusetts, which was 106,500 U.S. dollars in 2023. The average median household income in the United States was at 80,610 U.S. dollars.
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The Gross Domestic Product per capita in the United States was last recorded at 75491.61 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in the United States, when adjusted by Purchasing Power Parity is equivalent to 425 percent of the world's average. This dataset provides - United States GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Graph and download economic data for Real gross domestic product per capita (A939RX0Q048SBEA) from Q1 1947 to Q1 2025 about per capita, real, GDP, and USA.
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Context
The dataset presents median household incomes for various household sizes in State Line City, IN, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/state-line-city-in-median-household-income-by-household-size.jpeg" alt="State Line City, IN median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for State Line City median household income. You can refer the same here
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United States GDP by State per Capita: 2005p: Louisiana data was reported at 43,145.000 USD in 2012. This records an increase from the previous number of 42,764.000 USD for 2011. United States GDP by State per Capita: 2005p: Louisiana data is updated yearly, averaging 41,652.000 USD from Dec 1997 (Median) to 2012, with 16 observations. The data reached an all-time high of 44,723.000 USD in 2006 and a record low of 37,439.000 USD in 1997. United States GDP by State per Capita: 2005p: Louisiana data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A174: NIPA 2009: Gross Domestic Product by State: Per Capita.
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Graph and download economic data for Personal income per capita (A792RC0A052NBEA) from 1929 to 2024 about personal income, per capita, personal, income, GDP, and USA.
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Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2023 about personal income, personal, median, income, real, and USA.
Table from the American Community Survey (ACS) B19301 and B19313 per capita and aggregate income. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): B19301 and B19313Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.
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Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in United States: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for United States median household income by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in State Center. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in State Center. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in State Center, householders within the 45 to 64 years age group have the highest median household income at $125,313, followed by those in the 25 to 44 years age group with an income of $97,868. Meanwhile householders within the under 25 years age group report the second lowest median household income of $41,125. Notably, householders within the 65 years and over age group, had the lowest median household income at $36,912.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for State Center median household income by age. You can refer the same here
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United States US: GDP: GNI per Capita data was reported at 60,197.862 USD in 2017. This records an increase from the previous number of 58,652.956 USD for 2016. United States US: GDP: GNI per Capita data is updated yearly, averaging 22,170.343 USD from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 60,197.862 USD in 2017 and a record low of 3,024.282 USD in 1960. United States US: GDP: GNI per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Nominal. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ;
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Personal Income in the United States decreased 0.40 percent in May of 2025 over the previous month. This dataset provides the latest reported value for - United States Personal Income - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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Structural Change is the phenomenon witnessed by almost all the developing and the developed states in their journey towards a higher sustained economic growth. The rise in per capita income and the structural change are complementary to each other. A rise in per capita income reinforces structural change and structural change leads to the rise in the productive efficiency stimulating rise in the per capita income of the people. The paper analyses this phenomenon in the state of Bihar which has, of late, started ta witness a higher growth trajectory in its economy. Sourcing the data from the archival records of the various government agencies, the study found that the state of Bihar has mirrored the structural change being experienced by the economy of India. The share of the primary sector in the state's GSDP has drastically declined and is replaced by the services sector. This phenomenon is particularly ascribed to the rising share of trade, communications and the government led public spending in the construction sector. However, the state is not experiencing a balanced growth pattern in its economy; some districts have become more developed relative to the other districts. It has also been seen that due to the low economic base of the state, we cannot expect that the state's socio-economic indicators will converge sooner to the_ more developed states of India.
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NSDP Per Capita: Uttar Pradesh data was reported at 93,422.086 INR in 2024. This records an increase from the previous number of 83,056.934 INR for 2023. NSDP Per Capita: Uttar Pradesh data is updated yearly, averaging 57,944.312 INR from Mar 2012 (Median) to 2024, with 13 observations. The data reached an all-time high of 93,422.086 INR in 2024 and a record low of 32,002.002 INR in 2012. NSDP Per Capita: Uttar Pradesh data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under Global Database’s India – Table IN.GEI004: Memo Items: State Economy: Net State Domestic Product per Capita.
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Chad TD: GDP: USD: Gross National Income per Capita: Atlas Method data was reported at 670.000 USD in 2023. This records an increase from the previous number of 660.000 USD for 2022. Chad TD: GDP: USD: Gross National Income per Capita: Atlas Method data is updated yearly, averaging 220.000 USD from Dec 1962 (Median) to 2023, with 62 observations. The data reached an all-time high of 940.000 USD in 2014 and a record low of 110.000 USD in 1964. Chad TD: GDP: USD: Gross National Income per Capita: Atlas Method data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Gross Domestic Product: Nominal. GNI per capita (formerly GNP per capita) is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the midyear population. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;
This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in State College. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in State College. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in State College, householders within the 45 to 64 years age group have the highest median household income at $115,096, followed by those in the 65 years and over age group with an income of $86,164. Meanwhile householders within the 25 to 44 years age group report the second lowest median household income of $59,508. Notably, householders within the under 25 years age group, had the lowest median household income at $19,616.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for State College median household income by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
NSDP Per Capita: Tamil Nadu data was reported at 358,026.808 INR in 2025. This records an increase from the previous number of 315,219.594 INR for 2024. NSDP Per Capita: Tamil Nadu data is updated yearly, averaging 184,824.243 INR from Mar 2012 (Median) to 2025, with 14 observations. The data reached an all-time high of 358,026.808 INR in 2025 and a record low of 93,112.408 INR in 2012. NSDP Per Capita: Tamil Nadu data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under Global Database’s India – Table IN.GEI004: Memo Items: State Economy: Net State Domestic Product per Capita.
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Household Income per Capita: Avg per Month: NW: Kaliningrad Region data was reported at 52,023.000 RUB in 2024. This records an increase from the previous number of 38,367.000 RUB for 2023. Household Income per Capita: Avg per Month: NW: Kaliningrad Region data is updated yearly, averaging 14,771.700 RUB from Dec 1994 (Median) to 2024, with 31 observations. The data reached an all-time high of 52,023.000 RUB in 2024 and a record low of 167.700 RUB in 1994. Household Income per Capita: Avg per Month: NW: Kaliningrad Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA012: Household Income per Capita: by Region: Annual.
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License information was derived automatically
The Gross Domestic Product per capita in the United States was last recorded at 66682.61 US dollars in 2024. The GDP per Capita in the United States is equivalent to 528 percent of the world's average. This dataset provides - United States GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.